Predictor variables | Estimate | SE | β^{*} | t Value | p Value |
Model 1 | |||||
Constant | 0.31 | 0.003 | – | 114.28 | <0.0001 |
Log proportion of Hispanic | 0.91 | 0.01 | 0.29 | 68.52 | <0.0001 |
Log proportion of black | 0.43 | 0.01 | 0.17 | 41.74 | <0.0001 |
Log proportion of families living in poverty | 0.83 | 0.02 | 0.16 | 34.29 | <0.0001 |
Log proportion of women older than 25 years without a high school diploma | 0.34 | 0.02 | 0.09 | 17.33 | <0.0001 |
Log average household size | −0.57 | 0.01 | −0.18 | −54.02 | <0.0001 |
Urban (1=urban, 0=rural) | 0.32 | 0.003 | 0.33 | 93.90 | <0.0001 |
Model 2 | |||||
Constant | 0.26 | 0.003 | – | 81.38 | <0.0001 |
Log proportion of Hispanic | 0.11 | 0.03 | 0.03 | 4.12 | <0.0001 |
Log proportion of black | 0.10 | 0.02 | 0.04 | 4.13 | <0.0001 |
Log proportion of families living in poverty | 0.75 | 0.05 | 0.15 | 15.11 | <0.0001 |
Log proportion of women older than 25 years without a high school diploma | 0.05 | 0.04 | 0.01 | 1.33 | 0.183 |
Log average household size | −0.26 | 0.02 | −0.08 | −12.53 | <0.0001 |
Urban (1=urban, 0=rural) | 0.36 | 0.004 | 0.37 | 97.97 | <0.0001 |
Urban by log proportion of Hispanic | 1.01 | 0.03 | 0.29 | 33.16 | <0.0001 |
Urban by log proportion of black | 0.43 | 0.03 | 0.15 | 16.65 | <0.0001 |
Urban by log proportion of families living in poverty | 0.03 | 0.06 | 0.005 | 0.50 | 0.617 |
Urban by log proportion of women older than 25 years without a high school diploma | 0.33 | 0.04 | 0.08 | 7.73 | <0.0001 |
Urban by log average household size | −0.44 | 0.02 | −0.13 | −18.35 | <0.0001 |
R^{2}=0.39 for Step 1, ∆R^{2}=0.02 (p<0.0001).
The column header Estimate is the unstandardised parameter estimate. For all predictor variables except the binary urban/non-urban variable, the estimate represents the per cent change in the tobacco outlet density per 1000 population for a 1% change in the predictor variable since both the predictor and the outcome variables are log transformed. In the case of the binary urban/non-urban predictor variable, which is not log transformed, the estimate is the (100 × estimate) per cent change in the outcome variable for a unit change in the predictor variable. For the interaction terms, the interpretation is the additional percentage increase for urban census tracts versus rural census tracts. Thus, for instance, a 1% increase in the proportion of Hispanics in non-urban census tracts is associated with a 0.11% increase in the tobacco outlet density per 1000 population. For urban communities, there is an additional 1.01% change totalling to a 1.12% increase for a 1% increase in the proportion of Hispanics compared with a 0.11% increase in non-urban census tracts.
↵* Standardized parameter estimate.